Legal claims defining the scope of protection. Each claim is shown in both the original legal language and a plain English translation.
1. A computer-implemented method comprising: receiving a message at a mobile computing device; performing natural language processing (NLP) based interpretation of the message via the mobile computing device; generating a suggestion of an action to be performed via an application of the mobile computing device, the action based upon, at least in part, the NLP-based interpretation of the message; providing the suggestion to a user of the mobile computing device for user acceptance based upon, at least in part, one or more user-configurable settings stored on computer storage set by the user receiving the message; receiving user acceptance of the suggestion of the action; and activating the application in response to receiving the user acceptance of the suggestion to enable the performance of the action via the application.
This invention relates to mobile computing devices and methods for processing messages to generate actionable suggestions. The problem addressed is the inefficiency of manually interpreting messages and performing related actions on mobile devices, which often requires switching between applications and manual input. The solution involves a computer-implemented method that receives a message on a mobile device, processes it using natural language processing (NLP) to interpret its content, and generates a suggested action based on the interpretation. The suggestion is tailored to the user's preferences, which are stored in configurable settings. The user can accept or reject the suggestion. Upon acceptance, the relevant application is activated to execute the action, such as opening a link, creating a calendar event, or sending a reply. The method streamlines workflows by automating responses to messages while allowing user control over the suggested actions. The system ensures that the suggestions align with user preferences, enhancing usability and reducing manual effort. This approach is particularly useful for productivity and communication applications, where quick and accurate responses are critical.
2. The computer-implemented method of claim 1 , wherein the message is one or more of an MMS message, an SMS message, an instant message, and an email message.
This invention relates to a computer-implemented method for processing and analyzing messages exchanged between users, particularly focusing on different types of digital communications. The method addresses the challenge of efficiently categorizing and managing various message formats in a unified system, ensuring seamless integration and analysis across multiple communication channels. The method involves receiving a message from a user, where the message can be one or more of an MMS (Multimedia Messaging Service) message, an SMS (Short Message Service) message, an instant message, or an email message. The system processes these messages by extracting relevant data, such as content, metadata, and sender/receiver information, to facilitate further analysis or action. This allows for consistent handling of diverse message types, improving interoperability and functionality in communication platforms. By supporting multiple message formats, the method enables users to interact through their preferred communication channels while ensuring that the system can uniformly process and respond to each type. This enhances user experience and system efficiency, particularly in applications requiring cross-platform communication, such as customer service, enterprise messaging, or social media interactions. The method may also include additional steps like filtering, routing, or storing messages based on their type and content, further optimizing communication workflows.
3. The computer-implemented method of claim 1 , wherein the NLP-based interpretation is performed on the mobile computing device.
This invention relates to natural language processing (NLP) systems for interpreting user inputs, particularly in mobile computing environments. The problem addressed is the need for efficient, localized NLP interpretation to reduce latency and improve responsiveness in mobile applications. Traditional NLP systems often rely on cloud-based processing, which introduces delays due to network transmission and remote computation. This invention improves upon prior art by performing NLP-based interpretation directly on the mobile computing device, eliminating the need for external processing. The method involves receiving a user input, such as speech or text, and processing it locally using NLP techniques to extract meaning, intent, or commands. The mobile device executes the necessary algorithms to parse and interpret the input without relying on external servers. This approach enhances privacy, reduces dependency on network connectivity, and improves real-time performance. The invention may also include preprocessing steps to optimize input data for local NLP analysis, such as noise reduction or formatting adjustments. The system may further adapt to user preferences or usage patterns to refine interpretation accuracy over time. By performing NLP interpretation on the mobile device itself, the invention provides faster, more reliable, and more secure processing compared to cloud-based alternatives.
4. The computer-implemented method of claim 1 , wherein the NLP-based interpretation is performed on a server that is in communication with the mobile computing device.
This invention relates to natural language processing (NLP) systems for interpreting user inputs on mobile devices. The problem addressed is the limited computational resources of mobile devices, which can hinder accurate NLP-based interpretation of user queries or commands. The solution involves offloading the NLP processing to a remote server that communicates with the mobile device, enabling more sophisticated and resource-intensive NLP techniques to be applied without overburdening the mobile device's hardware. The method includes receiving a user input, such as a voice command or text query, on a mobile computing device. The input is transmitted to a remote server, where an NLP-based interpretation is performed. This interpretation may involve tasks such as semantic analysis, intent recognition, or entity extraction. The server processes the input using advanced NLP models that require significant computational power, which would be impractical to run directly on the mobile device. After processing, the server transmits the interpreted results back to the mobile device, which then executes an action based on the interpretation, such as providing a response, performing a task, or retrieving relevant data. By offloading the NLP workload to a server, the method ensures that the mobile device remains responsive and energy-efficient while still benefiting from high-accuracy NLP capabilities. This approach is particularly useful for applications like virtual assistants, voice-controlled applications, or any system requiring real-time language understanding on resource-constrained devices.
5. The computer-implemented method of claim 1 , wherein the suggestion is performed audibly via a virtual assistant associated with the mobile computing device.
This invention relates to a computer-implemented method for providing audible suggestions via a virtual assistant on a mobile computing device. The method addresses the problem of users needing real-time, context-aware assistance while interacting with their mobile devices, particularly in situations where visual interaction may be impractical or unsafe, such as while driving or multitasking. The method involves analyzing user behavior, device usage patterns, or environmental context to generate relevant suggestions. These suggestions are then delivered audibly through a virtual assistant integrated with the mobile device. The virtual assistant processes the suggestions and presents them to the user in a spoken format, allowing for hands-free interaction. The system may also adapt the timing, content, or delivery method of the suggestions based on user preferences, historical data, or real-time conditions to enhance usability and relevance. The method may further include confirming user intent before executing suggested actions, ensuring that the virtual assistant only performs tasks when explicitly authorized. This ensures a balance between automation and user control. The system may also learn from user responses to improve future suggestions, creating a personalized and adaptive assistance experience. By leveraging audible suggestions through a virtual assistant, the invention enhances user convenience, safety, and efficiency, particularly in scenarios where visual interaction is limited. The method integrates seamlessly with existing mobile computing devices and virtual assistant technologies, providing an intuitive and responsive assistance framework.
6. The computer-implemented method of claim 1 , wherein at least one of performing and generating are automatically triggered upon receipt of the message.
This invention relates to automated message processing in computer systems, specifically addressing the need for efficient and timely responses to incoming messages without manual intervention. The method involves automatically triggering at least one of two actions—performing a task or generating a response—upon receiving a message. The system monitors incoming messages and, based on predefined criteria or rules, initiates the appropriate action without requiring user input. This automation streamlines workflows by reducing delays and human error, particularly in environments where rapid response times are critical, such as customer service, data processing, or real-time communication systems. The method may involve analyzing the message content, extracting relevant data, and executing predefined operations like data updates, notifications, or generating formatted replies. The automation ensures consistency and reliability in handling messages, improving system efficiency and user experience. The invention is particularly useful in scenarios where immediate action is necessary, such as alert systems, transaction processing, or interactive applications.
7. The computer-implemented method of claim 1 , further comprising: activating the application automatically without requiring user acceptance of the suggestion.
This invention relates to computer-implemented methods for automatically activating applications based on user behavior or context, eliminating the need for manual user acceptance. The method addresses the problem of inefficiency in application launch processes, where users must manually confirm or accept suggestions before an application can be opened. This delay disrupts workflow and reduces productivity, particularly in environments where quick access to applications is critical. The method involves detecting a triggering event, such as user activity or system state, that indicates a likely need for a specific application. Based on this event, the system generates a suggestion to activate the application. Unlike conventional systems that require explicit user confirmation, this method automatically activates the application without waiting for user input. This ensures seamless and immediate access, improving efficiency and reducing interruptions. The underlying system may include components for monitoring user behavior, analyzing context, and determining the most relevant application to launch. The automatic activation is triggered by predefined rules or machine learning models trained to predict user needs. The method ensures that the application is launched in a state ready for immediate use, further enhancing productivity. This approach is particularly useful in scenarios where rapid access to applications is essential, such as in professional or high-pressure environments. By removing the need for manual confirmation, the method streamlines workflows and reduces cognitive load on users. The invention improves user experience by making application access faster and more intuitive.
8. The computer-implemented method of claim 1 , further comprising: connecting the mobile computing device with a third party server.
This invention relates to mobile computing devices and methods for enhancing their functionality through server connectivity. The problem addressed is the limited capabilities of mobile devices when operating in isolation, particularly in tasks requiring external data processing, storage, or specialized services. The solution involves a computer-implemented method where a mobile computing device establishes a connection with a third-party server to access additional resources or services. This connection enables the mobile device to offload tasks, retrieve data, or utilize cloud-based applications that extend its functionality beyond local processing. The method may include authentication steps to ensure secure access to the server, as well as data transmission protocols to facilitate efficient communication. By integrating with external servers, the mobile device can perform operations that would otherwise be impractical or impossible due to hardware or software limitations. This approach improves performance, scalability, and versatility for mobile applications, particularly in scenarios requiring real-time processing, large-scale data analysis, or specialized computational tasks. The invention is applicable in fields such as mobile computing, cloud computing, and distributed systems.
9. The computer-implemented method of claim 1 , wherein the suggestion is displayed on a graphical user interface associated with the mobile computing device.
A computer-implemented method provides a solution for enhancing user interaction with mobile computing devices by generating and displaying context-aware suggestions. The method involves analyzing user behavior, device usage patterns, and environmental data to identify opportunities for improving efficiency or convenience. Based on this analysis, the system generates tailored suggestions, such as shortcuts, automation options, or reminders, which are then presented to the user. These suggestions are displayed on a graphical user interface (GUI) of the mobile device, ensuring they are easily accessible and actionable. The method may also involve prioritizing suggestions based on relevance, urgency, or user preferences to optimize engagement. By dynamically adapting to the user's context, the system reduces manual effort and enhances productivity. The approach leverages machine learning or rule-based logic to refine suggestions over time, improving accuracy and personalization. This method is particularly useful in scenarios where users need quick access to relevant actions or information without navigating complex menus or performing repetitive tasks. The GUI integration ensures suggestions are seamlessly incorporated into the user's workflow, minimizing disruption while maximizing utility.
10. The computer-implemented method of claim 1 , wherein the one or more preferences includes at least one of classifying the action, connecting the mobile computing device with one of a third party server, service provider, and the application, how to perform the action when the message is sent from a particular user, and how to perform the action based on a type of the message.
This invention relates to a computer-implemented method for managing actions triggered by messages received by a mobile computing device. The method addresses the problem of efficiently processing and responding to messages based on user preferences, ensuring actions are performed in a context-aware manner. The system classifies incoming messages and executes predefined actions, such as connecting the device to a third-party server, service provider, or application, based on user-defined rules. These rules may include classifying the action, determining how to perform the action when the message originates from a specific user, or adjusting the action based on the message type. The method dynamically adapts responses to messages, improving user experience by automating interactions while maintaining flexibility in how actions are executed. The system ensures that actions are performed in a controlled and customizable manner, reducing manual intervention and enhancing efficiency in message processing.
11. A non-transitory computer-readable storage medium having a plurality of instructions stored thereon that when executed by a processor, cause the processor to perform operations comprising: receiving a message at a mobile computing device; performing natural language processing (NLP) based interpretation of the message via the mobile computing device; generating a suggestion of an action to be performed via an application of the mobile computing device, the action based upon, at least in part, the NLP-based interpretation of the message; providing the suggestion to a user of the mobile computing device based upon, at least in part, one or more user-configurable settings stored on computer storage set by the user receiving the message; receiving user acceptance of the suggestion of the action; and activating the application in response to receiving the user acceptance of the suggestion to enable the performance of the action via the application.
This invention relates to mobile computing devices and systems for processing and responding to messages using natural language processing (NLP) to suggest and execute actions. The problem addressed is the inefficiency of manually interpreting messages and performing related actions on mobile devices, which often requires switching between applications or manual input. The solution involves a mobile computing device that receives a message and performs NLP-based interpretation to understand its content. Based on this interpretation, the device generates a suggestion for an action that can be performed via an application installed on the device. The suggestion is presented to the user according to configurable settings, such as preferred actions or application preferences. If the user accepts the suggestion, the corresponding application is automatically activated, and the action is performed. The system allows for seamless integration of message interpretation with action execution, reducing user effort and improving efficiency. The user-configurable settings ensure personalized and relevant suggestions, enhancing usability. The invention leverages NLP to bridge the gap between message content and actionable tasks, streamlining workflows on mobile devices.
12. The non-transitory computer-readable storage medium of claim 11 , wherein the message is one or more of an MMS message, an SMS message, an instant message, and an email message.
The invention relates to a system for processing and analyzing messages exchanged between users, particularly focusing on different types of digital communications. The system captures and stores messages such as MMS (Multimedia Messaging Service), SMS (Short Message Service), instant messages, and emails. These messages are then analyzed to extract relevant data, which may include content, metadata, or user interaction patterns. The extracted data is used to generate insights, such as sentiment analysis, user behavior trends, or content categorization. The system may also apply machine learning techniques to improve the accuracy of message classification or to detect anomalies in communication patterns. The stored messages and derived insights can be used for various purposes, including security monitoring, customer service improvements, or marketing analytics. The invention ensures that the messages are processed in a way that preserves their original context while enabling efficient analysis and retrieval. The system may also include features for handling large volumes of messages, ensuring scalability and performance. The invention addresses the need for automated message analysis in environments where manual review is impractical, providing a scalable solution for extracting valuable information from digital communications.
13. The non-transitory computer-readable storage medium of claim 11 , wherein the NLP-based interpretation is performed on the mobile computing device.
This invention relates to natural language processing (NLP) systems for interpreting user inputs on mobile computing devices. The problem addressed is the need for efficient, localized NLP interpretation to reduce latency and improve responsiveness in mobile applications. Traditional systems often rely on cloud-based NLP processing, which introduces delays due to network transmission and remote computation. The invention improves upon this by performing NLP-based interpretation directly on the mobile device, leveraging local processing power to minimize latency and enhance user experience. The system includes a mobile computing device with a processor and memory storing instructions for NLP-based interpretation. The device receives user input, such as voice or text, and processes it locally using NLP techniques to extract meaning, intent, or context. This local processing avoids the need for external server communication, reducing dependency on network conditions and improving real-time performance. The invention may also include preprocessing steps to optimize input data for NLP analysis, such as noise reduction or formatting adjustments, ensuring accurate interpretation even in resource-constrained environments. The NLP-based interpretation may involve tasks like intent recognition, entity extraction, or semantic analysis, tailored to the specific application, such as virtual assistants, chatbots, or voice-controlled interfaces. By executing these tasks on the device, the system ensures faster response times and greater privacy, as sensitive data does not need to be transmitted to external servers. The invention is particularly useful in scenarios where network connectivity is unreliable or where low-latency processing is critical.
14. The non-transitory computer-readable storage medium of claim 11 , wherein the NLP-based interpretation is performed on a server that is in communication with the mobile computing device.
This invention relates to natural language processing (NLP) systems for interpreting user inputs on mobile devices. The problem addressed is the limited computational resources of mobile devices, which can hinder accurate NLP-based interpretation of user queries or commands. The solution involves offloading the NLP processing to a remote server that communicates with the mobile device, thereby leveraging more powerful computing resources while maintaining real-time responsiveness. The system includes a mobile computing device that captures user input, such as speech or text, and transmits it to a remote server. The server performs NLP-based interpretation, which may involve tasks like semantic analysis, intent recognition, or entity extraction. The interpreted results are then sent back to the mobile device for further processing or action. The server may also access additional data sources or knowledge bases to enhance interpretation accuracy. This approach ensures that resource-intensive NLP tasks are handled efficiently without overburdening the mobile device, improving performance and user experience. The system may be applied in various applications, including virtual assistants, chatbots, or voice-controlled interfaces.
15. The non-transitory computer-readable storage medium of claim 11 , wherein the suggestion is performed audibly via a virtual assistant associated with the mobile computing device.
A system provides a virtual assistant for a mobile computing device that audibly suggests actions or information to a user based on contextual data. The virtual assistant processes data from the mobile device, such as location, time, user behavior, or external inputs, to determine relevant suggestions. These suggestions are then delivered audibly through the device's audio output, allowing hands-free interaction. The system may also integrate with other applications or services to enhance suggestion accuracy and relevance. The virtual assistant can adapt its responses based on user preferences, historical data, or real-time conditions, ensuring personalized and timely assistance. This technology addresses the need for seamless, voice-based interaction in mobile environments, improving user convenience and efficiency. The system may further include mechanisms to prioritize suggestions, filter irrelevant inputs, or confirm user intent before executing actions, ensuring a smooth and intuitive experience. By leveraging contextual awareness and voice output, the system enhances accessibility and usability for users in various scenarios, such as navigation, reminders, or task management.
16. A computing system, comprising: one or more processors configured to receive a message at a mobile computing device, the one or more processors further configured to perform natural language processing (NLP) based interpretation of the message via the mobile computing device, the one or more processors further configured to generate a suggestion of an action to be performed via an application of the mobile computing device, the action based upon, at least in part, the NLP-based interpretation of the message, the one or more processors further configured to provide the suggestion to a user of the mobile computing device based upon, at least in part, one or more user-configurable settings stored on computer storage set by the user receiving the message, the one or more processors further configured to receive user acceptance of the suggestion of the action, the one or more processors further configured to activate the application in response to receiving the user acceptance of the suggestion to enable the performance of the action via the application.
The computing system processes messages on a mobile device using natural language processing (NLP) to interpret the content and generate actionable suggestions. The system analyzes incoming messages to determine relevant actions, such as scheduling an event, sending a reply, or opening an application. These suggestions are tailored based on user-configurable settings, allowing customization of the system's behavior. When a user accepts a suggestion, the system automatically activates the appropriate application to execute the action, streamlining workflows. The NLP interpretation ensures context-aware recommendations, while user preferences control the system's responsiveness. This approach enhances productivity by reducing manual steps in message processing and application activation. The system integrates message analysis, action suggestion, and application automation into a cohesive workflow, adapting to user preferences for personalized efficiency.
17. The system of claim 16 , wherein at least one of performing and generating are automatically triggered upon receipt of the message.
A system for automated message processing in a communication network addresses the problem of manual intervention in handling incoming messages, which can lead to delays and inefficiencies. The system includes a message receiver configured to obtain messages from a communication network, a processor coupled to the message receiver, and a memory storing instructions executable by the processor. The processor is configured to perform at least one action based on the received message, such as analyzing the message content, extracting relevant data, or generating a response. Additionally, the system can automatically trigger the performance of these actions or the generation of outputs upon receiving the message, eliminating the need for manual initiation. This automation streamlines workflows, reduces response times, and improves system reliability by ensuring consistent processing of incoming messages. The system may also include a user interface for configuring the automated actions or reviewing processed results, enhancing flexibility and user control. The overall solution is particularly useful in environments where rapid and accurate message handling is critical, such as customer service, logistics, or financial transactions.
18. The system of claim 16 , wherein the one or more processors are further configured to activate the application automatically without requiring user acceptance of the suggestion.
This invention relates to automated application activation in computing systems. The problem addressed is the need to streamline user workflows by reducing manual intervention when launching applications, particularly in scenarios where user context or system state suggests a specific application should be opened. The system includes one or more processors configured to monitor user activity, system state, or external triggers to generate suggestions for application activation. These suggestions are generated based on predefined rules, historical usage patterns, or contextual data. The system further includes a user interface component that presents these suggestions to the user, allowing them to accept or reject them. The invention improves upon prior systems by enabling automatic activation of the suggested application without requiring explicit user confirmation, thereby enhancing efficiency and reducing interruptions. This automatic activation is triggered when certain conditions are met, such as the user's current task, time of day, or system events, ensuring seamless integration into the user's workflow. The system may also include mechanisms to learn and adapt these activation rules over time based on user behavior, further optimizing the automation process. This approach is particularly useful in environments where rapid access to applications is critical, such as enterprise or productivity-focused settings.
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September 22, 2020
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